we present an accurate and efficient solution for pose estimation from line features. By introducing coplanarity errors, we formulate
the objective functions in terms of distances in the 3D scene space, and use different optimization strategies to find the best rotation and
translation. Experiments show that the algorithm has strong robustness to noise and outliers, and that it can attain very accurate results
efficiently.